lines.survfit            package:survival            R Documentation

_A_d_d _L_i_n_e_s _o_r _P_o_i_n_t_s _t_o _a _S_u_r_v_i_v_a_l _P_l_o_t

_D_e_s_c_r_i_p_t_i_o_n:

     Often used to add the expected survival curve(s) to a Kaplan-Meier
     plot generated with 'plot.survfit'.

_U_s_a_g_e:

     ## S3 method for class 'survfit':
     lines(x, type="s", mark=3, col=1, lty=1,
     lwd=1, mark.time=TRUE , xscale=1,  firstx=0, firsty=1, xmax, fun, conf.int=FALSE,  ...)
     ## S3 method for class 'survfit':
     points(x, ...)

_A_r_g_u_m_e_n_t_s:

       x: a survival object, generated from the 'survfit' or 'survexp'
          functions. 

    type: the line type, as described in 'lines'.  The default is a
          step function for 'survfit' objects, and a connected line for
          'survexp' objects. 

    mark: vectors giving the mark symbol, color, line type and line
          width for the added curves. 

mark.time: controls the labeling of the curves.   If 'FALSE', no
          labeling is done.   If 'TRUE', then curves are marked at each
          censoring time.   If 'mark.time' is a numeric vector, then
          curves are marked at  the specified time points. 

  xscale: a number used to divide the x values.  If time was originally
          in days, a value of 365.24 would give a plotted scale in
          years. 

firstx,firsty: the starting point for the survival curves.  If either
          of these is set to 'NA' or <blank> the plot will start at the
          first time point of the curve. 

col,lty,lwd,...: passed to 'lines'

    xmax: the maximum horizontal plot coordinate.     This shortens the
          curve before plotting it, so unlike using the 'xlim'
          graphical parameter, warning messages about out of bounds
          points are not generated. 

     fun: an arbitrary function defining a transformation of the
          survival curve. For example 'fun=log' is an alternative way
          to draw a log-survival curve (but with the axis labeled with
          log(S) values). Four often used transformations can be
          specified with a character argument instead: '"log"' is the
          same as using the 'log=T' option, '"event"' plots cumulative
          events (f(y) =1-y), '"cumhaz"' plots the cumulative hazard
          function (f(y) = -log(y)) and '"cloglog"' creates a
          complementary log-log survival plot  (f(y) = log(-log(y))
          along with log scale for the x-axis).

conf.int: if TRUE, confidence bands for the curves are also plotted. If
          set to '"only"', then only the CI bands are plotted, and the
          curve itself is left off.   This can be useful for fine
          control over the colors or line types of a plot. 

_V_a_l_u_e:

     a list with components 'x' and 'y', containing the coordinates of
     the last point on each of the curves (but not of the confidence
     limits). This may be useful for labeling.

_S_i_d_e _E_f_f_e_c_t_s:

     one or more curves are added to the current plot.

_S_e_e _A_l_s_o:

     'lines', 'par', 'plot.survfit', 'survfit', 'survexp'.

_E_x_a_m_p_l_e_s:

     data(pbc)
     fit <- survfit(Surv(time, status) ~ sex, pbc,subset=1:312)
     plot(fit, mark.time=FALSE, xscale=365.24,
             xlab='Years', ylab='Survival')
     lines(fit[1], lwd=2, xscale=365.24)    #darken the first curve and add marks

     # add expected survival curves for the two groups,
     #   based on the US expected
     tdata <- data.frame(age=pbc$age*365.24, sex=pbc$sex +1,
                         year= rep(mdy.date(1,1,1976), nrow(pbc)))
     tdata<-tdata[1:312,] ## only the randomised people, with no missing data
     data(ratetables)
     efit <- survexp(~ sex+ratetable(sex=sex,age=age,year=year), data=tdata, ratetable=survexp.us, times=(0:24)*182)
     temp <- lines(efit, lty=2, xscale=365.24, lwd=2:1)
     text(temp, c("Male", "Female"), adj= -.1) #labels just past the ends
     title(main="Primary Biliary Cirrhosis, Observed and Expected")

